Nowadays, backup technology has been broadly used in the information technology. Traditional backup systems back up data with a fixed time interval, which creates a time gap between the last and the next backup time. However, if any system failure occurred in the foregoing time gap, the data changes happened in between the last backup and the failure event will not be able to be recovered.
Moreover, the prior art backup systems usually support incremental backup. With incremental backup, only changed data will be backed up for less storage and network consumption. However, to identify changed data requires additional comparisons and calculations which usually need more storage and computing resources to perform.
When executing data restore process, the prior art backup systems allow restore the metadata of the backup data firstly for a faster data restore. However, behind the faster data restore, the whole backup data still need to be asynchronously transferred from a backup storage to a restore target, which usually takes a long time to process. Before the backup data being fully restored, the system using the restored storage cannot get the same storage access performance as the system operated before the failure event.
Accordingly, to provide a better backup method for avoiding the aforementioned problems is needed in this field.